Our contributions are summarized as follows: 1. We reformulate the bilevel optimization in [1]} by excluding the inequality constraints in the lower-level problem, which leads to drastically reduced computation time for an optimal solution. 2. We use analytical gradients in the upper-level problem to simultaneously update the spatial and temporal assignment, which is more accurate and efficient than using finite-difference methods or other numerical approximations.
